----------------------------------------------------------------------------------------------------------------------------------
      name:  <unnamed>
       log:  C:\Users\Dr. Badas\Dropbox\1 - Research\98 - Coauthored Projects\1 - Gender and Law Clerk Encouragement\2- Data and C
> ode\First Survey\BadasStaufferJLCreplication.log
  log type:  text
 opened on:   7 Dec 2021, 15:10:23

. 
. use "BadasStauffer-GenderClerkAmbition-JLC-DATAFILE.dta"

. 
. ///: Table 1 
> ///: Models of ambition for each institution 
> logit SC_ambition i.Female   White LawYear ClerkWork TotalGroup Age ideology Legal_Inter  i.CatRank

Iteration 0:   log likelihood = -85.828079  
Iteration 1:   log likelihood =  -74.42038  
Iteration 2:   log likelihood =  -72.10756  
Iteration 3:   log likelihood = -72.081876  
Iteration 4:   log likelihood = -72.081849  
Iteration 5:   log likelihood = -72.081849  

Logistic regression                             Number of obs     =        235
                                                LR chi2(13)       =      27.49
                                                Prob > chi2       =     0.0106
Log likelihood = -72.081849                     Pseudo R2         =     0.1602

--------------------------------------------------------------------------------
   SC_ambition |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
---------------+----------------------------------------------------------------
      1.Female |  -1.351454   .4924878    -2.74   0.006    -2.316712   -.3861955
         White |   .3745784    .629818     0.59   0.552    -.8598422    1.608999
       LawYear |   .0387358   .4836498     0.08   0.936    -.9092003     .986672
 ClerkWorkshop |   -.158268    .867621    -0.18   0.855    -1.858774    1.542238
   TotalGroups |   .2703248    .186383     1.45   0.147    -.0949791    .6356288
           Age |   -.082884   .0943237    -0.88   0.380     -.267755    .1019871
      ideology |   .3362216   .1385895     2.43   0.015     .0645913     .607852
Legal_Interest |   .1820848   .2581417     0.71   0.481    -.3238635    .6880332
               |
       CatRank |
            2  |  -.8814339   .7328675    -1.20   0.229    -2.317828    .5549601
            3  |  -1.668494   .7371649    -2.26   0.024    -3.113311   -.2236774
            4  |  -.5371168   .7116559    -0.75   0.450    -1.931937    .8577032
            5  |  -1.600567   1.107044    -1.45   0.148    -3.770333    .5691995
            6  |  -.8202462   .8582362    -0.96   0.339    -2.502358    .8618657
               |
         _cons |  -1.029227   2.700446    -0.38   0.703    -6.322004     4.26355
--------------------------------------------------------------------------------

. margins,dydx(Female) plot

Average marginal effects                        Number of obs     =        235
Model VCE    : OIM

Expression   : Pr(SC_ambition), predict()
dy/dx w.r.t. : 1.Female

------------------------------------------------------------------------------
             |            Delta-method
             |      dy/dx   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
    1.Female |  -.1317975   .0502487    -2.62   0.009    -.2302831   -.0333118
------------------------------------------------------------------------------
Note: dy/dx for factor levels is the discrete change from the base level.

  Variables that uniquely identify margins:
(note:  named style line not found in class linepattern, default attributes used)

. eststo SC

. 
. logit COA_ambition i.Female  White LawYear ClerkWork TotalGroup Age ideology Legal_Inter  i.CatRank

Iteration 0:   log likelihood = -161.95004  
Iteration 1:   log likelihood = -125.08449  
Iteration 2:   log likelihood = -124.79696  
Iteration 3:   log likelihood = -124.79674  
Iteration 4:   log likelihood = -124.79674  

Logistic regression                             Number of obs     =        235
                                                LR chi2(13)       =      74.31
                                                Prob > chi2       =     0.0000
Log likelihood = -124.79674                     Pseudo R2         =     0.2294

--------------------------------------------------------------------------------
  COA_ambition |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
---------------+----------------------------------------------------------------
      1.Female |  -.7357609   .3526861    -2.09   0.037    -1.427013   -.0445088
         White |   2.039333   .4977332     4.10   0.000     1.063794    3.014872
       LawYear |   .2948021   .3398868     0.87   0.386    -.3713639     .960968
 ClerkWorkshop |   1.125451   .5085372     2.21   0.027     .1287368    2.122166
   TotalGroups |   .4141682   .1290143     3.21   0.001     .1613049    .6670314
           Age |  -.1436585    .062466    -2.30   0.021    -.2660897   -.0212273
      ideology |   .0501833   .1097839     0.46   0.648    -.1649891    .2653557
Legal_Interest |   .5184562   .1860976     2.79   0.005     .1537117    .8832007
               |
       CatRank |
            2  |   -1.90169   .5513374    -3.45   0.001    -2.982292   -.8210889
            3  |  -2.000092   .4747006    -4.21   0.000    -2.930488   -1.069695
            4  |  -2.354657   .5755626    -4.09   0.000    -3.482739   -1.226575
            5  |  -2.312362   .5866677    -3.94   0.000     -3.46221   -1.162515
            6  |  -2.428981   .6082092    -3.99   0.000    -3.621049   -1.236913
               |
         _cons |   .9499204   1.809975     0.52   0.600    -2.597565    4.497406
--------------------------------------------------------------------------------

. margins Female

Predictive margins                              Number of obs     =        235
Model VCE    : OIM

Expression   : Pr(COA_ambition), predict()

------------------------------------------------------------------------------
             |            Delta-method
             |     Margin   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
      Female |
          0  |   .6277804   .0467031    13.44   0.000     .5362439    .7193168
          1  |   .4959639   .0363251    13.65   0.000     .4247681    .5671597
------------------------------------------------------------------------------

. 
. eststo COA

. 
. logit DCT_ambition i.Female  White LawYear  ClerkWork TotalGroup Age ideology Legal_Inter i.CatRank

Iteration 0:   log likelihood = -158.93329  
Iteration 1:   log likelihood = -143.64065  
Iteration 2:   log likelihood = -143.55958  
Iteration 3:   log likelihood = -143.55957  

Logistic regression                             Number of obs     =        235
                                                LR chi2(13)       =      30.75
                                                Prob > chi2       =     0.0037
Log likelihood = -143.55957                     Pseudo R2         =     0.0967

--------------------------------------------------------------------------------
  DCT_ambition |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
---------------+----------------------------------------------------------------
      1.Female |  -.1452289   .3167054    -0.46   0.647    -.7659601    .4755023
         White |   .4708494   .4144855     1.14   0.256    -.3415273    1.283226
       LawYear |  -.1208469   .3099365    -0.39   0.697    -.7283113    .4866175
 ClerkWorkshop |    .332921   .4682449     0.71   0.477    -.5848222    1.250664
   TotalGroups |   .3337092   .1221531     2.73   0.006     .0942935    .5731248
           Age |  -.0491523   .0481719    -1.02   0.308    -.1435675    .0452629
      ideology |  -.2372347   .0970894    -2.44   0.015    -.4275264    -.046943
Legal_Interest |   .4091883   .1686023     2.43   0.015     .0787338    .7396429
               |
       CatRank |
            2  |   -.654167   .4861857    -1.35   0.178    -1.607073    .2987394
            3  |  -.5830194   .3985935    -1.46   0.144    -1.364248    .1982094
            4  |  -.0429811   .4831945    -0.09   0.929    -.9900248    .9040627
            5  |  -.2234434   .5267716    -0.42   0.671    -1.255897    .8090099
            6  |  -.5129355   .5388721    -0.95   0.341    -1.569105    .5432344
               |
         _cons |   .8071005   1.515261     0.53   0.594    -2.162756    3.776957
--------------------------------------------------------------------------------

. margins, dydx(Female) plot

Average marginal effects                        Number of obs     =        235
Model VCE    : OIM

Expression   : Pr(DCT_ambition), predict()
dy/dx w.r.t. : 1.Female

------------------------------------------------------------------------------
             |            Delta-method
             |      dy/dx   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
    1.Female |  -.0305683   .0662641    -0.46   0.645    -.1604436    .0993069
------------------------------------------------------------------------------
Note: dy/dx for factor levels is the discrete change from the base level.

  Variables that uniquely identify margins:

. 
. eststo DCT

. 
. logit SSC_ambition i.Female White LawYear  ClerkWork TotalGroup Age ideology Legal_Inter  i.CatRank

Iteration 0:   log likelihood = -143.97423  
Iteration 1:   log likelihood = -130.73715  
Iteration 2:   log likelihood = -130.47028  
Iteration 3:   log likelihood = -130.46982  
Iteration 4:   log likelihood = -130.46982  

Logistic regression                             Number of obs     =        235
                                                LR chi2(13)       =      27.01
                                                Prob > chi2       =     0.0124
Log likelihood = -130.46982                     Pseudo R2         =     0.0938

--------------------------------------------------------------------------------
  SSC_ambition |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
---------------+----------------------------------------------------------------
      1.Female |   .1134504   .3397903     0.33   0.738    -.5525264    .7794272
         White |   .0001847   .4505709     0.00   1.000     -.882918    .8832874
       LawYear |  -.3215827   .3263954    -0.99   0.324    -.9613058    .3181405
 ClerkWorkshop |  -.1256723     .48714    -0.26   0.796    -1.080449    .8291046
   TotalGroups |   .1779748   .1226926     1.45   0.147    -.0624984    .4184479
           Age |  -.0234259   .0523629    -0.45   0.655    -.1260553    .0792035
      ideology |  -.1844523   .1100374    -1.68   0.094    -.4001216     .031217
Legal_Interest |   .1710413   .1835486     0.93   0.351    -.1887074    .5307899
               |
       CatRank |
            2  |   .4019608   .5630381     0.71   0.475    -.7015737    1.505495
            3  |   .8659195   .4341288     1.99   0.046     .0150427    1.716796
            4  |   1.374101   .4905999     2.80   0.005      .412543    2.335659
            5  |   2.017812     .53995     3.74   0.000      .959529    3.076094
            6  |    .639859   .5976153     1.07   0.284    -.5314454    1.811163
               |
         _cons |  -.5307185   1.624683    -0.33   0.744    -3.715039    2.653602
--------------------------------------------------------------------------------

. margins, dydx(Female) plot

Average marginal effects                        Number of obs     =        235
Model VCE    : OIM

Expression   : Pr(SSC_ambition), predict()
dy/dx w.r.t. : 1.Female

------------------------------------------------------------------------------
             |            Delta-method
             |      dy/dx   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
    1.Female |   .0211124   .0630742     0.33   0.738    -.1025107    .1447355
------------------------------------------------------------------------------
Note: dy/dx for factor levels is the discrete change from the base level.

  Variables that uniquely identify margins:

. 
. eststo SSC

. 
. 
. logit OSC_ambition i.Female White LawYear  ClerkWork TotalGroup Age ideology Legal_Inter  i.CatRank

note: 2.CatRank != 0 predicts failure perfectly
      2.CatRank dropped and 26 obs not used

Iteration 0:   log likelihood = -91.157926  
Iteration 1:   log likelihood = -76.588265  
Iteration 2:   log likelihood = -73.673104  
Iteration 3:   log likelihood = -73.590919  
Iteration 4:   log likelihood = -73.590417  
Iteration 5:   log likelihood = -73.590417  

Logistic regression                             Number of obs     =        209
                                                LR chi2(12)       =      35.14
                                                Prob > chi2       =     0.0004
Log likelihood = -73.590417                     Pseudo R2         =     0.1927

--------------------------------------------------------------------------------
  OSC_ambition |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
---------------+----------------------------------------------------------------
      1.Female |   .0326473   .4761167     0.07   0.945    -.9005243    .9658188
         White |   .6454968   .7294773     0.88   0.376    -.7842524    2.075246
       LawYear |  -.3044949   .4488818    -0.68   0.498    -1.184287    .5752972
 ClerkWorkshop |   -2.42777   1.070773    -2.27   0.023    -4.526446   -.3290944
   TotalGroups |   .0024112   .1580351     0.02   0.988    -.3073318    .3121543
           Age |    .041673   .0570264     0.73   0.465    -.0700967    .1534426
      ideology |  -.1237379   .1492184    -0.83   0.407    -.4162007    .1687248
Legal_Interest |  -.1948468   .2627984    -0.74   0.458    -.7099223    .3202286
               |
       CatRank |
            2  |          0  (empty)
            3  |   .9614717    .683947     1.41   0.160    -.3790398    2.301983
            4  |   2.511983   .6841312     3.67   0.000     1.171111    3.852856
            5  |    2.74734   .6988793     3.93   0.000     1.377562    4.117118
            6  |   1.794502   .8062869     2.23   0.026     .2142089    3.374796
               |
         _cons |  -2.993532   1.942078    -1.54   0.123    -6.799935    .8128714
--------------------------------------------------------------------------------

. margins, dydx(Female) plot

Average marginal effects                        Number of obs     =        209
Model VCE    : OIM

Expression   : Pr(OSC_ambition), predict()
dy/dx w.r.t. : 1.Female

------------------------------------------------------------------------------
             |            Delta-method
             |      dy/dx   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
    1.Female |    .003541   .0515609     0.07   0.945    -.0975165    .1045986
------------------------------------------------------------------------------
Note: dy/dx for factor levels is the discrete change from the base level.

  Variables that uniquely identify margins:

. 
. eststo OSC

. 
. 
.   
.   
. ///:Table 2
> ///: Models for Qualification at each institution
> reg qualified_SC Female White LawYear ClerkWork TotalGroup Age ideology Legal_Inter Encouragement i.Cat

      Source |       SS           df       MS      Number of obs   =       235
-------------+----------------------------------   F(14, 220)      =      3.98
       Model |  27.7127713        14  1.97948366   Prob > F        =    0.0000
    Residual |  109.351058       220  .497050266   R-squared       =    0.2022
-------------+----------------------------------   Adj R-squared   =    0.1514
       Total |   137.06383       234  .585742862   Root MSE        =    .70502

--------------------------------------------------------------------------------
  qualified_SC |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
---------------+----------------------------------------------------------------
        Female |  -.0099464   .1030381    -0.10   0.923    -.2130145    .1931218
         White |   .1513217   .1354105     1.12   0.265     -.115546    .4181895
       LawYear |    .101879   .1000412     1.02   0.310    -.0952829    .2990408
 ClerkWorkshop |   .1511755   .1472065     1.03   0.306    -.1389399    .4412909
   TotalGroups |  -.0060065   .0385573    -0.16   0.876    -.0819955    .0699824
           Age |   .0398295    .015648     2.55   0.012     .0089904    .0706686
      ideology |   .0812738   .0317571     2.56   0.011     .0186868    .1438608
Legal_Interest |   .1022067   .0551544     1.85   0.065    -.0064919    .2109052
 Encouragement |   .6011523    .222283     2.70   0.007     .1630758    1.039229
               |
       CatRank |
            2  |  -.3948723    .161728    -2.44   0.015    -.7136067   -.0761378
            3  |  -.6016474   .1306239    -4.61   0.000    -.8590816   -.3442131
            4  |  -.2922234   .1536949    -1.90   0.059    -.5951263    .0106794
            5  |  -.5109088   .1703403    -3.00   0.003    -.8466165   -.1752011
            6  |  -.6864952   .1791007    -3.83   0.000    -1.039468   -.3335226
               |
         _cons |  -.2855473   .4886125    -0.58   0.560    -1.248508     .677413
--------------------------------------------------------------------------------

. eststo qsc

. 
. reg qualified_COA Female White LawYear ClerkWork TotalGroup Age ideology Legal_Inter Encouragement i.CatRank

      Source |       SS           df       MS      Number of obs   =       235
-------------+----------------------------------   F(14, 220)      =      6.35
       Model |  57.2632855        14  4.09023468   Prob > F        =    0.0000
    Residual |  141.817566       220  .644625298   R-squared       =    0.2876
-------------+----------------------------------   Adj R-squared   =    0.2423
       Total |  199.080851       234  .850772868   Root MSE        =    .80289

--------------------------------------------------------------------------------
 qualified_COA |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
---------------+----------------------------------------------------------------
        Female |  -.1603165   .1173415    -1.37   0.173    -.3915737    .0709408
         White |   .4409363   .1542076     2.86   0.005     .1370231    .7448496
       LawYear |   .2291439   .1139285     2.01   0.046     .0046129    .4536749
 ClerkWorkshop |   .3330438   .1676411     1.99   0.048     .0026558    .6634318
   TotalGroups |   .0204457   .0439097     0.47   0.642    -.0660918    .1069831
           Age |   .0310433   .0178201     1.74   0.083    -.0040767    .0661633
      ideology |   .0806188   .0361655     2.23   0.027     .0093437    .1518939
Legal_Interest |   .0647934   .0628107     1.03   0.303    -.0589943     .188581
 Encouragement |   .9941295   .2531394     3.93   0.000     .4952409    1.493018
               |
       CatRank |
            2  |  -.3500697   .1841784    -1.90   0.059    -.7130496    .0129101
            3  |  -.7938225   .1487565    -5.34   0.000    -1.086993   -.5006523
            4  |  -.7018294   .1750302    -4.01   0.000     -1.04678   -.3568788
            5  |  -.8465266   .1939863    -4.36   0.000    -1.228836   -.4642174
            6  |  -1.122826   .2039627    -5.51   0.000    -1.524797   -.7208555
               |
         _cons |   .4337395   .5564397     0.78   0.437    -.6628949    1.530374
--------------------------------------------------------------------------------

. eststo qcoa

. 
. reg qualified_DCT Female White LawYear ClerkWork TotalGroup Age ideology Legal_Inter Encouragement i.CatRank

      Source |       SS           df       MS      Number of obs   =       235
-------------+----------------------------------   F(14, 220)      =      4.77
       Model |   30.576454        14  2.18403243   Prob > F        =    0.0000
    Residual |  100.785248       220  .458114764   R-squared       =    0.2328
-------------+----------------------------------   Adj R-squared   =    0.1839
       Total |  131.361702       234  .561374795   Root MSE        =    .67684

--------------------------------------------------------------------------------
 qualified_DCT |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
---------------+----------------------------------------------------------------
        Female |  -.1813591   .0989202    -1.83   0.068    -.3763115    .0135934
         White |   .3124061   .1299988     2.40   0.017     .0562038    .5686085
       LawYear |   .1155686   .0960431     1.20   0.230    -.0737136    .3048508
 ClerkWorkshop |   .2797413   .1413234     1.98   0.049     .0012205    .5582622
   TotalGroups |   .0116694   .0370163     0.32   0.753    -.0612826    .0846215
           Age |   .0091363   .0150226     0.61   0.544    -.0204703    .0387429
      ideology |    .075321   .0304879     2.47   0.014     .0152353    .1354067
Legal_Interest |   .0109552   .0529501     0.21   0.836    -.0933992    .1153096
 Encouragement |   1.082667   .2133994     5.07   0.000     .6620982    1.503236
               |
       CatRank |
            2  |   .0949269   .1552645     0.61   0.542    -.2110693     .400923
            3  |  -.3790335   .1254035    -3.02   0.003    -.6261793   -.1318877
            4  |  -.3052034   .1475525    -2.07   0.040    -.5960006   -.0144061
            5  |  -.4344073   .1635327    -2.66   0.008    -.7566984   -.1121162
            6  |  -.2793781   .1719429    -1.62   0.106    -.6182441    .0594879
               |
         _cons |   1.838178    .469085     3.92   0.000     .9137022    2.762653
--------------------------------------------------------------------------------

. eststo qdct

. 
. reg qualified_SSC Female White LawYear ClerkWork TotalGroup Age ideology Legal_Inter Encouragement i.CatRank

      Source |       SS           df       MS      Number of obs   =       235
-------------+----------------------------------   F(14, 220)      =      3.99
       Model |  27.2138956        14  1.94384969   Prob > F        =    0.0000
    Residual |  107.313764       220  .487789836   R-squared       =    0.2023
-------------+----------------------------------   Adj R-squared   =    0.1515
       Total |   134.52766       234  .574904528   Root MSE        =    .69842

--------------------------------------------------------------------------------
 qualified_SSC |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
---------------+----------------------------------------------------------------
        Female |  -.1248264   .1020738    -1.22   0.223     -.325994    .0763412
         White |   .4110651   .1341432     3.06   0.002     .1466949    .6754352
       LawYear |    .112517   .0991049     1.14   0.257    -.0827996    .3078335
 ClerkWorkshop |   .1813653   .1458288     1.24   0.215    -.1060348    .4687654
   TotalGroups |   .0234855   .0381964     0.61   0.539    -.0517923    .0987632
           Age |  -.0117568   .0155015    -0.76   0.449    -.0423072    .0187937
      ideology |   .0807083   .0314598     2.57   0.011     .0187071    .1427096
Legal_Interest |  -.0351609   .0546382    -0.64   0.521    -.1428421    .0725204
 Encouragement |   .9641126   .2202026     4.38   0.000     .5301361    1.398089
               |
       CatRank |
            2  |     .27514   .1602143     1.72   0.087    -.0406113    .5908914
            3  |  -.2573875   .1294013    -1.99   0.048    -.5124123   -.0023626
            4  |  -.2363578   .1522565    -1.55   0.122    -.5364257    .0637101
            5  |  -.1101645   .1687461    -0.65   0.515    -.4427302    .2224012
            6  |  -.2504647   .1774244    -1.41   0.159    -.6001338    .0992043
               |
         _cons |   2.520561   .4840395     5.21   0.000     1.566613    3.474509
--------------------------------------------------------------------------------

. eststo qssc

. 
. reg qualified_OSC Female White LawYear ClerkWork TotalGroup Age ideology Legal_Inter Encouragement i.CatRank

      Source |       SS           df       MS      Number of obs   =       235
-------------+----------------------------------   F(14, 220)      =      2.75
       Model |  18.2590181        14  1.30421558   Prob > F        =    0.0009
    Residual |   104.25162       220  .473871001   R-squared       =    0.1490
-------------+----------------------------------   Adj R-squared   =    0.0949
       Total |  122.510638       234  .523549736   Root MSE        =    .68838

--------------------------------------------------------------------------------
 qualified_OSC |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
---------------+----------------------------------------------------------------
        Female |  -.1225911   .1006069    -1.22   0.224    -.3208678    .0756856
         White |   .1474526   .1322155     1.12   0.266    -.1131184    .4080236
       LawYear |   .0882999   .0976807     0.90   0.367    -.1042099    .2808096
 ClerkWorkshop |   .1542105   .1437331     1.07   0.284    -.1290596    .4374805
   TotalGroups |   .0031266   .0376475     0.08   0.934    -.0710693    .0773226
           Age |  -.0061527   .0152787    -0.40   0.688    -.0362641    .0239588
      ideology |   .0810645   .0310078     2.61   0.010     .0199542    .1421747
Legal_Interest |  -.0073171    .053853    -0.14   0.892    -.1134509    .0988167
 Encouragement |   .8227386   .2170382     3.79   0.000     .3949985    1.250479
               |
       CatRank |
            2  |    .248613    .157912     1.57   0.117    -.0626008    .5598268
            3  |  -.0803651   .1275418    -0.63   0.529    -.3317251    .1709949
            4  |  -.1031253   .1500685    -0.69   0.493     -.398881    .1926305
            5  |   .1054194   .1663211     0.63   0.527    -.2223672     .433206
            6  |    .025144   .1748747     0.14   0.886    -.3195001    .3697881
               |
         _cons |   2.761317   .4770836     5.79   0.000     1.821078    3.701556
--------------------------------------------------------------------------------

. eststo qosc

. 
. esttab qsc qcoa qdct qssc qosc using clerktable.tex, se label replace booktabs ///
>   alignment(D{.}{.}{-1})                         ///
>   title(OLS Regression: Perceived Qualification\label{Qualifications})
(output written to clerktable.tex)

.   
. ///: Table 3
> ///: Encouragement
> reg Encouragement i.Female White LawYear ClerkWork TotalGroup Age ideology Legal_Inter i.CatRank

      Source |       SS           df       MS      Number of obs   =       236
-------------+----------------------------------   F(13, 222)      =      2.75
       Model |  1.62127198        13  .124713229   Prob > F        =    0.0012
    Residual |  10.0800352       222  .045405564   R-squared       =    0.1386
-------------+----------------------------------   Adj R-squared   =    0.0881
       Total |  11.7013071       235  .049792796   Root MSE        =    .21309

--------------------------------------------------------------------------------
 Encouragement |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
---------------+----------------------------------------------------------------
      1.Female |   .0136901   .0310623     0.44   0.660    -.0475246    .0749049
         White |   .0432526   .0407985     1.06   0.290    -.0371492    .1236545
       LawYear |  -.0015207   .0301829    -0.05   0.960    -.0610024    .0579609
 ClerkWorkshop |  -.0121504   .0444652    -0.27   0.785    -.0997783    .0754775
   TotalGroups |   .0337577   .0114191     2.96   0.003      .011254    .0562615
           Age |   .0091495   .0046894     1.95   0.052    -.0000919    .0183908
      ideology |   .0108931   .0095663     1.14   0.256    -.0079594    .0297456
Legal_Interest |   .0377338   .0164665     2.29   0.023     .0052831    .0701845
               |
       CatRank |
            2  |   .0015648    .048821     0.03   0.974    -.0946471    .0977767
            3  |   .0488069   .0392263     1.24   0.215    -.0284967    .1261105
            4  |  -.0221742   .0463545    -0.48   0.633    -.1135253    .0691769
            5  |   .0943423   .0510071     1.85   0.066    -.0061777    .1948624
            6  |    .102202   .0536307     1.91   0.058    -.0034884    .2078924
               |
         _cons |  -.0188094   .1473828    -0.13   0.899    -.3092579     .271639
--------------------------------------------------------------------------------

. 
. 
. eststo encouragement

. 
.   
.  ///: Table 4 
>  ///: Interaction Qualification and Gender
>  logit SC_ambition i.Female##c.qualified_SC  White LawYear ClerkWork TotalGroup Age ideology Legal_Inter Encouragement i.CatRank

Iteration 0:   log likelihood = -85.700924  
Iteration 1:   log likelihood = -65.181671  
Iteration 2:   log likelihood = -57.826375  
Iteration 3:   log likelihood = -56.801684  
Iteration 4:   log likelihood = -56.793893  
Iteration 5:   log likelihood = -56.793885  
Iteration 6:   log likelihood = -56.793885  

Logistic regression                             Number of obs     =        234
                                                LR chi2(16)       =      57.81
                                                Prob > chi2       =     0.0000
Log likelihood = -56.793885                     Pseudo R2         =     0.3373

---------------------------------------------------------------------------------------
          SC_ambition |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
----------------------+----------------------------------------------------------------
             1.Female |  -1.031655   1.502221    -0.69   0.492    -3.975954    1.912644
         qualified_SC |    1.53836   .4698815     3.27   0.001     .6174089     2.45931
                      |
Female#c.qualified_SC |
                   1  |  -.3626956    .672417    -0.54   0.590    -1.680609    .9552174
                      |
                White |   .2843865   .7135938     0.40   0.690    -1.114232    1.683005
              LawYear |  -.3157715   .5628183    -0.56   0.575    -1.418875     .787332
        ClerkWorkshop |  -.5949647   .9738615    -0.61   0.541    -2.503698    1.313769
          TotalGroups |   .1990496   .2119156     0.94   0.348    -.2162973    .6143966
                  Age |  -.1569249   .1079731    -1.45   0.146    -.3685483    .0546984
             ideology |   .1885926   .1637984     1.15   0.250    -.1324464    .5096316
       Legal_Interest |  -.2008095    .296487    -0.68   0.498    -.7819132    .3802943
        Encouragement |   3.514833   1.438333     2.44   0.015     .6957517    6.333915
                      |
              CatRank |
                   2  |  -.5030087   .8274876    -0.61   0.543    -2.124855    1.118837
                   3  |  -1.233885   .8262329    -1.49   0.135    -2.853271    .3855021
                   4  |  -.0894916   .8208048    -0.11   0.913     -1.69824    1.519256
                   5  |  -2.020927   1.561189    -1.29   0.195    -5.080801    1.038948
                   6  |  -.5824949   .9939104    -0.59   0.558    -2.530524    1.365534
                      |
                _cons |  -1.266324   2.978533    -0.43   0.671    -7.104142    4.571493
---------------------------------------------------------------------------------------

. margins, dydx(Female) at(qualified_SC=(1(1)4)) plot

Average marginal effects                        Number of obs     =        234
Model VCE    : OIM

Expression   : Pr(SC_ambition), predict()
dy/dx w.r.t. : 1.Female

1._at        : qualified_SC    =           1

2._at        : qualified_SC    =           2

3._at        : qualified_SC    =           3

4._at        : qualified_SC    =           4

------------------------------------------------------------------------------
             |            Delta-method
             |      dy/dx   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
0.Female     |  (base outcome)
-------------+----------------------------------------------------------------
1.Female     |
         _at |
          1  |  -.0516765   .0378856    -1.36   0.173    -.1259309    .0225779
          2  |  -.1714281   .0569075    -3.01   0.003    -.2829647   -.0598915
          3  |  -.3545587   .1333751    -2.66   0.008    -.6159691   -.0931484
          4  |  -.4502913   .2228006    -2.02   0.043    -.8869724   -.0136102
------------------------------------------------------------------------------
Note: dy/dx for factor levels is the discrete change from the base level.

  Variables that uniquely identify margins: qualified_SC

. eststo SC_q

. 
. logit COA_ambition i.Female##c.qualified_COA White LawYear ClerkWork TotalGroup Age ideology Legal_Inter Encouragement i.CatRank

Iteration 0:   log likelihood = -161.16072  
Iteration 1:   log likelihood = -112.90368  
Iteration 2:   log likelihood = -112.22491  
Iteration 3:   log likelihood =  -112.2233  
Iteration 4:   log likelihood =  -112.2233  

Logistic regression                             Number of obs     =        234
                                                LR chi2(16)       =      97.87
                                                Prob > chi2       =     0.0000
Log likelihood =  -112.2233                     Pseudo R2         =     0.3037

----------------------------------------------------------------------------------------
          COA_ambition |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-----------------------+----------------------------------------------------------------
              1.Female |  -1.374259   1.100995    -1.25   0.212    -3.532169    .7836515
         qualified_COA |   .3671205    .308461     1.19   0.234    -.2374519    .9716929
                       |
Female#c.qualified_COA |
                    1  |   .2276131   .3941845     0.58   0.564    -.5449744    1.000201
                       |
                 White |   2.006992   .5419897     3.70   0.000     .9447119    3.069272
               LawYear |   .2010542   .3642098     0.55   0.581    -.5127839    .9148923
         ClerkWorkshop |   1.139707   .5694714     2.00   0.045     .0235634     2.25585
           TotalGroups |   .3523618   .1371743     2.57   0.010      .083505    .6212185
                   Age |  -.2137791   .0716262    -2.98   0.003    -.3541639   -.0733943
              ideology |  -.0064917   .1201645    -0.05   0.957    -.2420098    .2290265
        Legal_Interest |   .3937397    .196022     2.01   0.045     .0095435    .7779358
         Encouragement |   2.766001   .8728813     3.17   0.002     1.055185    4.476817
                       |
               CatRank |
                    2  |  -2.116226   .6029681    -3.51   0.000    -3.298021   -.9344297
                    3  |  -2.044468   .5273543    -3.88   0.000    -3.078064   -1.010873
                    4  |  -2.248669   .6416575    -3.50   0.000    -3.506294   -.9910433
                    5  |  -2.462736   .6497847    -3.79   0.000    -3.736291   -1.189182
                    6  |  -2.570826   .6971974    -3.69   0.000    -3.937308   -1.204345
                       |
                 _cons |   1.486375   2.040572     0.73   0.466    -2.513073    5.485823
----------------------------------------------------------------------------------------

. margins, dydx(Female) at(qualified_COA=(1(1)4)) plot

Average marginal effects                        Number of obs     =        234
Model VCE    : OIM

Expression   : Pr(COA_ambition), predict()
dy/dx w.r.t. : 1.Female

1._at        : qualified_~A    =           1

2._at        : qualified_~A    =           2

3._at        : qualified_~A    =           3

4._at        : qualified_~A    =           4

------------------------------------------------------------------------------
             |            Delta-method
             |      dy/dx   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
0.Female     |  (base outcome)
-------------+----------------------------------------------------------------
1.Female     |
         _at |
          1  |  -.1958841    .124146    -1.58   0.115    -.4392058    .0474376
          2  |  -.1592521   .0754887    -2.11   0.035    -.3072072    -.011297
          3  |  -.1154484   .0658526    -1.75   0.080     -.244517    .0136203
          4  |  -.0707979   .0997767    -0.71   0.478    -.2663567    .1247609
------------------------------------------------------------------------------
Note: dy/dx for factor levels is the discrete change from the base level.

  Variables that uniquely identify margins: qualified_COA

. 
. eststo COA_q

. 
. logit DCT_ambition i.Female##c.qualified_DCT White LawYear  ClerkWork TotalGroup Age ideology Legal_Inter Encouragement i.CatRan
> k

Iteration 0:   log likelihood = -158.03496  
Iteration 1:   log likelihood = -138.49955  
Iteration 2:   log likelihood = -138.36396  
Iteration 3:   log likelihood = -138.36384  
Iteration 4:   log likelihood = -138.36384  

Logistic regression                             Number of obs     =        234
                                                LR chi2(16)       =      39.34
                                                Prob > chi2       =     0.0010
Log likelihood = -138.36384                     Pseudo R2         =     0.1245

----------------------------------------------------------------------------------------
          DCT_ambition |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-----------------------+----------------------------------------------------------------
              1.Female |   .2669129   1.461737     0.18   0.855    -2.598038    3.131864
         qualified_DCT |   .1338669   .3854901     0.35   0.728    -.6216799    .8894136
                       |
Female#c.qualified_DCT |
                    1  |  -.1241243   .4376709    -0.28   0.777    -.9819435     .733695
                       |
                 White |   .3765365   .4299921     0.88   0.381    -.4662324    1.219305
               LawYear |  -.1694174   .3208501    -0.53   0.597    -.7982721    .4594373
         ClerkWorkshop |   .3812444   .4899585     0.78   0.437    -.5790566    1.341545
           TotalGroups |   .2688792    .125952     2.13   0.033     .0220179    .5157406
                   Age |  -.0698779   .0505129    -1.38   0.167    -.1688813    .0291255
              ideology |  -.2698625   .1014053    -2.66   0.008    -.4686133   -.0711117
        Legal_Interest |   .3435049    .173469     1.98   0.048     .0035119     .683498
         Encouragement |   2.006897   .7486499     2.68   0.007     .5395699    3.474224
                       |
               CatRank |
                    2  |  -.7080223   .4946294    -1.43   0.152    -1.677478    .2614336
                    3  |  -.7007985   .4177184    -1.68   0.093    -1.519512    .1179145
                    4  |   .0114723   .5012753     0.02   0.982    -.9710092    .9939538
                    5  |  -.4609209   .5554524    -0.83   0.407    -1.549588    .6277458
                    6  |  -.7472477   .5703452    -1.31   0.190    -1.865104    .3706082
                       |
                 _cons |   .6180665   1.827811     0.34   0.735    -2.964377     4.20051
----------------------------------------------------------------------------------------

. margins, dydx(Female) at(qualified_DCT=(1(1)4)) plot

Average marginal effects                        Number of obs     =        234
Model VCE    : OIM

Expression   : Pr(DCT_ambition), predict()
dy/dx w.r.t. : 1.Female

1._at        : qualified_~T    =           1

2._at        : qualified_~T    =           2

3._at        : qualified_~T    =           3

4._at        : qualified_~T    =           4

------------------------------------------------------------------------------
             |            Delta-method
             |      dy/dx   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
0.Female     |  (base outcome)
-------------+----------------------------------------------------------------
1.Female     |
         _at |
          1  |   .0295269   .2157995     0.14   0.891    -.3934324    .4524862
          2  |   .0038309   .1313833     0.03   0.977    -.2536756    .2613374
          3  |  -.0214428   .0701166    -0.31   0.760    -.1588688    .1159833
          4  |   -.046152   .0923995    -0.50   0.617    -.2272517    .1349477
------------------------------------------------------------------------------
Note: dy/dx for factor levels is the discrete change from the base level.

  Variables that uniquely identify margins: qualified_DCT

. 
. eststo DCT_q

. 
. logit SSC_ambition i.Female##c.qualified_SSC White LawYear ClerkWork TotalGroup Age ideology Legal_Inter Encouragement i.CatRank

Iteration 0:   log likelihood = -143.61359  
Iteration 1:   log likelihood = -130.51878  
Iteration 2:   log likelihood = -130.25556  
Iteration 3:   log likelihood = -130.25508  
Iteration 4:   log likelihood = -130.25508  

Logistic regression                             Number of obs     =        234
                                                LR chi2(16)       =      26.72
                                                Prob > chi2       =     0.0447
Log likelihood = -130.25508                     Pseudo R2         =     0.0930

----------------------------------------------------------------------------------------
          SSC_ambition |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-----------------------+----------------------------------------------------------------
              1.Female |   -.041987    1.48884    -0.03   0.978    -2.960059    2.876085
         qualified_SSC |    .014943   .3603931     0.04   0.967    -.6914145    .7213006
                       |
Female#c.qualified_SSC |
                    1  |   .0512022   .4279394     0.12   0.905    -.7875436     .889948
                       |
                 White |  -.0088884   .4647739    -0.02   0.985    -.9198284    .9020516
               LawYear |  -.3351937   .3278078    -1.02   0.307    -.9776852    .3072978
         ClerkWorkshop |  -.1430299   .4921814    -0.29   0.771    -1.107688    .8216279
           TotalGroups |   .1796794    .127505     1.41   0.159    -.0702259    .4295846
                   Age |  -.0219627   .0527518    -0.42   0.677    -.1253543     .081429
              ideology |  -.1847632   .1125907    -1.64   0.101    -.4054369    .0359105
        Legal_Interest |   .1751038   .1860546     0.94   0.347    -.1895565    .5397641
         Encouragement |   -.149076   .7579436    -0.20   0.844    -1.634618    1.336466
                       |
               CatRank |
                    2  |   .3800903   .5666199     0.67   0.502    -.7304642    1.490645
                    3  |   .8715768   .4418222     1.97   0.049     .0056213    1.737532
                    4  |   1.370317   .4957127     2.76   0.006     .3987375    2.341896
                    5  |   2.015429   .5476554     3.68   0.000     .9420437    3.088814
                    6  |   .6439124   .6109547     1.05   0.292    -.5535368    1.841362
                       |
                 _cons |  -.5176297   1.938107    -0.27   0.789    -4.316249    3.280989
----------------------------------------------------------------------------------------

. margins, dydx(Female) at(qualified_SSC=(1(1)4)) plot

Average marginal effects                        Number of obs     =        234
Model VCE    : OIM

Expression   : Pr(SSC_ambition), predict()
dy/dx w.r.t. : 1.Female

1._at        : qualifie~SSC    =           1

2._at        : qualifie~SSC    =           2

3._at        : qualifie~SSC    =           3

4._at        : qualifie~SSC    =           4

------------------------------------------------------------------------------
             |            Delta-method
             |      dy/dx   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
0.Female     |  (base outcome)
-------------+----------------------------------------------------------------
1.Female     |
         _at |
          1  |   .0016634   .1942632     0.01   0.993    -.3790855    .3824123
          2  |   .0110648   .1249561     0.09   0.929    -.2338448    .2559743
          3  |   .0207292   .0702532     0.30   0.768    -.1169646    .1584229
          4  |    .030646   .0809014     0.38   0.705    -.1279178    .1892099
------------------------------------------------------------------------------
Note: dy/dx for factor levels is the discrete change from the base level.

  Variables that uniquely identify margins: qualified_SSC

. 
. eststo SSC_q

. 
. 
. logit OSC_ambition i.Female##c.qualified_OSC White LawYear ClerkWork TotalGroup Age ideology Legal_Inter Encouragement i.CatRank

note: 2.CatRank != 0 predicts failure perfectly
      2.CatRank dropped and 26 obs not used

Iteration 0:   log likelihood = -90.985626  
Iteration 1:   log likelihood = -75.617462  
Iteration 2:   log likelihood = -72.426003  
Iteration 3:   log likelihood = -72.327794  
Iteration 4:   log likelihood = -72.327316  
Iteration 5:   log likelihood = -72.327316  

Logistic regression                             Number of obs     =        208
                                                LR chi2(15)       =      37.32
                                                Prob > chi2       =     0.0011
Log likelihood = -72.327316                     Pseudo R2         =     0.2051

----------------------------------------------------------------------------------------
          OSC_ambition |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-----------------------+----------------------------------------------------------------
              1.Female |  -2.109519   2.472633    -0.85   0.394     -6.95579    2.736753
         qualified_OSC |   .0526438   .5051945     0.10   0.917    -.9375192    1.042807
                       |
Female#c.qualified_OSC |
                    1  |   .6019844   .6758795     0.89   0.373     -.722715    1.926684
                       |
                 White |   .5403256   .7422491     0.73   0.467    -.9144559    1.995107
               LawYear |  -.4180697   .4627448    -0.90   0.366    -1.325033    .4888935
         ClerkWorkshop |  -2.527881   1.078932    -2.34   0.019    -4.642549   -.4132136
           TotalGroups |  -.0179086   .1671879    -0.11   0.915    -.3455909    .3097737
                   Age |    .034555   .0582604     0.59   0.553    -.0796333    .1487432
              ideology |  -.1399793    .153379    -0.91   0.361    -.4405965    .1606379
        Legal_Interest |  -.2006043    .267512    -0.75   0.453    -.7249181    .3237095
         Encouragement |   .1924769   1.046683     0.18   0.854    -1.858983    2.243937
                       |
               CatRank |
                    2  |          0  (empty)
                    3  |     .90521   .6956332     1.30   0.193    -.4582061    2.268626
                    4  |   2.624291   .7002092     3.75   0.000     1.251907    3.996676
                    5  |   2.642767   .7092001     3.73   0.000      1.25276    4.032773
                    6  |   1.650893   .8280989     1.99   0.046     .0278488    3.273937
                       |
                 _cons |  -2.568373    2.61587    -0.98   0.326    -7.695384    2.558637
----------------------------------------------------------------------------------------

. margins, dydx(Female) at(qualified_OSC=(1(1)4)) plot

Average marginal effects                        Number of obs     =        208
Model VCE    : OIM

Expression   : Pr(OSC_ambition), predict()
dy/dx w.r.t. : 1.Female

1._at        : qualifie~OSC    =           1

2._at        : qualifie~OSC    =           2

3._at        : qualifie~OSC    =           3

4._at        : qualifie~OSC    =           4

------------------------------------------------------------------------------
             |            Delta-method
             |      dy/dx   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
0.Female     |  (base outcome)
-------------+----------------------------------------------------------------
1.Female     |
         _at |
          1  |  -.1001974   .1416504    -0.71   0.479     -.377827    .1774322
          2  |   -.073822   .1013085    -0.73   0.466     -.272383    .1247389
          3  |  -.0298978   .0620092    -0.48   0.630    -.1514337    .0916381
          4  |   .0346643   .0635891     0.55   0.586    -.0899681    .1592967
------------------------------------------------------------------------------
Note: dy/dx for factor levels is the discrete change from the base level.

  Variables that uniquely identify margins: qualified_OSC

. 
. eststo OSC_q

. 
.   
.  ///: Table 5 
>  ///: Interaction encouragement and gender
>  logit SC_ambition i.Female##c.Encouragement qualified_SC  White LawYear ClerkWork TotalGroup Age ideology Legal_Inter i.CatRank

Iteration 0:   log likelihood = -85.700924  
Iteration 1:   log likelihood =  -64.28533  
Iteration 2:   log likelihood = -57.297465  
Iteration 3:   log likelihood = -56.862855  
Iteration 4:   log likelihood =  -56.85969  
Iteration 5:   log likelihood = -56.859688  

Logistic regression                             Number of obs     =        234
                                                LR chi2(16)       =      57.68
                                                Prob > chi2       =     0.0000
Log likelihood = -56.859688                     Pseudo R2         =     0.3365

----------------------------------------------------------------------------------------
           SC_ambition |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-----------------------+----------------------------------------------------------------
              1.Female |  -1.153427   1.669809    -0.69   0.490    -4.426193    2.119338
         Encouragement |   3.959841   1.865252     2.12   0.034     .3040131    7.615668
                       |
Female#c.Encouragement |
                    1  |  -1.077832    2.68122    -0.40   0.688    -6.332926    4.177262
                       |
          qualified_SC |   1.386809   .3492975     3.97   0.000     .7021981    2.071419
                 White |   .2969252   .7183146     0.41   0.679    -1.110946    1.704796
               LawYear |  -.3400665   .5645736    -0.60   0.547     -1.44661    .7664775
         ClerkWorkshop |  -.7053267   .9771765    -0.72   0.470    -2.620557    1.209904
           TotalGroups |   .2013516   .2124184     0.95   0.343    -.2149808     .617684
                   Age |  -.1490688   .1046389    -1.42   0.154    -.3541573    .0560198
              ideology |   .1868976   .1617854     1.16   0.248    -.1301959    .5039911
        Legal_Interest |  -.2009948   .2968192    -0.68   0.498    -.7827496    .3807601
                       |
               CatRank |
                    2  |  -.5107181   .8233108    -0.62   0.535    -2.124378    1.102941
                    3  |  -1.267342   .8268408    -1.53   0.125     -2.88792    .3532363
                    4  |   -.062039   .8107892    -0.08   0.939    -1.651157    1.527079
                    5  |  -1.956453   1.532158    -1.28   0.202    -4.959428    1.046522
                    6  |  -.6805216   .9846318    -0.69   0.489    -2.610364    1.249321
                       |
                 _cons |  -1.352693   2.968895    -0.46   0.649    -7.171621    4.466234
----------------------------------------------------------------------------------------

. margins, dydx(Female) at(Encouragement=(0(.1)1)) plot(recast(line) recastci(rarea))

Average marginal effects                        Number of obs     =        234
Model VCE    : OIM

Expression   : Pr(SC_ambition), predict()
dy/dx w.r.t. : 1.Female

1._at        : Encouragem~t    =           0

2._at        : Encouragem~t    =          .1

3._at        : Encouragem~t    =          .2

4._at        : Encouragem~t    =          .3

5._at        : Encouragem~t    =          .4

6._at        : Encouragem~t    =          .5

7._at        : Encouragem~t    =          .6

8._at        : Encouragem~t    =          .7

9._at        : Encouragem~t    =          .8

10._at       : Encouragem~t    =          .9

11._at       : Encouragem~t    =           1

------------------------------------------------------------------------------
             |            Delta-method
             |      dy/dx   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
0.Female     |  (base outcome)
-------------+----------------------------------------------------------------
1.Female     |
         _at |
          1  |  -.0282165   .0433147    -0.65   0.515    -.1131118    .0566787
          2  |  -.0397829   .0474391    -0.84   0.402    -.1327618    .0531959
          3  |  -.0549395   .0497755    -1.10   0.270    -.1524977    .0426187
          4  |  -.0743537    .049787    -1.49   0.135    -.1719346    .0232271
          5  |    -.09861   .0477785    -2.06   0.039    -.1922542   -.0049658
          6  |  -.1280639   .0464528    -2.76   0.006    -.2191098    -.037018
          7  |  -.1626653    .052236    -3.11   0.002    -.2650459   -.0602847
          8  |    -.20181   .0704686    -2.86   0.004    -.3399259   -.0636941
          9  |  -.2442777   .0998528    -2.45   0.014    -.4399856   -.0485698
         10  |  -.2882705   .1364034    -2.11   0.035    -.5556163   -.0209248
         11  |  -.3315325   .1764919    -1.88   0.060    -.6774504    .0143853
------------------------------------------------------------------------------
Note: dy/dx for factor levels is the discrete change from the base level.

  Variables that uniquely identify margins: Encouragement

. eststo SC_encour

. 
. logit COA_ambition i.Female##c.Encouragement qualified_COA White LawYear ClerkWork TotalGroup Age ideology Legal_Inter i.CatRank

Iteration 0:   log likelihood = -161.16072  
Iteration 1:   log likelihood = -112.85757  
Iteration 2:   log likelihood = -112.07942  
Iteration 3:   log likelihood = -112.07732  
Iteration 4:   log likelihood = -112.07732  

Logistic regression                             Number of obs     =        234
                                                LR chi2(16)       =      98.17
                                                Prob > chi2       =     0.0000
Log likelihood = -112.07732                     Pseudo R2         =     0.3046

----------------------------------------------------------------------------------------
          COA_ambition |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-----------------------+----------------------------------------------------------------
              1.Female |  -1.477642   .9653178    -1.53   0.126     -3.36963    .4143464
         Encouragement |   1.933838    1.36164     1.42   0.156     -.734928    4.602604
                       |
Female#c.Encouragement |
                    1  |   1.330803   1.682562     0.79   0.429    -1.966958    4.628564
                       |
         qualified_COA |   .4946328    .211322     2.34   0.019     .0804493    .9088164
                 White |   2.030412   .5439329     3.73   0.000     .9643232    3.096501
               LawYear |   .2229766   .3658126     0.61   0.542     -.494003    .9399561
         ClerkWorkshop |   1.239747   .5787881     2.14   0.032     .1053427     2.37415
           TotalGroups |   .3468461   .1360849     2.55   0.011     .0801245    .6135676
                   Age |  -.2208417   .0731675    -3.02   0.003    -.3642473   -.0774361
              ideology |  -.0003082   .1202251    -0.00   0.998    -.2359451    .2353286
        Legal_Interest |   .4042236   .1968931     2.05   0.040     .0183202     .790127
                       |
               CatRank |
                    2  |  -2.100842   .6045287    -3.48   0.001    -3.285697   -.9159876
                    3  |  -2.043216   .5298465    -3.86   0.000    -3.081696   -1.004736
                    4  |   -2.30059   .6465823    -3.56   0.000    -3.567868   -1.033312
                    5  |  -2.472044   .6447496    -3.83   0.000     -3.73573   -1.208358
                    6  |  -2.552937   .6940155    -3.68   0.000    -3.913183   -1.192692
                       |
                 _cons |   1.648462   2.078491     0.79   0.428    -2.425306     5.72223
----------------------------------------------------------------------------------------

. margins, dydx(Female) at(Encouragement=(0(.1)1)) plot(recast(line) recastci(rarea))

Average marginal effects                        Number of obs     =        234
Model VCE    : OIM

Expression   : Pr(COA_ambition), predict()
dy/dx w.r.t. : 1.Female

1._at        : Encouragem~t    =           0

2._at        : Encouragem~t    =          .1

3._at        : Encouragem~t    =          .2

4._at        : Encouragem~t    =          .3

5._at        : Encouragem~t    =          .4

6._at        : Encouragem~t    =          .5

7._at        : Encouragem~t    =          .6

8._at        : Encouragem~t    =          .7

9._at        : Encouragem~t    =          .8

10._at       : Encouragem~t    =          .9

11._at       : Encouragem~t    =           1

------------------------------------------------------------------------------
             |            Delta-method
             |      dy/dx   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
0.Female     |  (base outcome)
-------------+----------------------------------------------------------------
1.Female     |
         _at |
          1  |  -.2177457   .1434916    -1.52   0.129    -.4989841    .0634927
          2  |  -.2073627   .1245994    -1.66   0.096     -.451573    .0368477
          3  |   -.193725   .1049409    -1.85   0.065    -.3994053    .0119553
          4  |   -.176919   .0859101    -2.06   0.039    -.3452996   -.0085383
          5  |  -.1572072   .0700498    -2.24   0.025    -.2945024   -.0199121
          6  |  -.1350895   .0614606    -2.20   0.028      -.25555    -.014629
          7  |  -.1113162    .063481    -1.75   0.080    -.2357366    .0131043
          8  |  -.0868397   .0742245    -1.17   0.242     -.232317    .0586376
          9  |  -.0627103   .0886987    -0.71   0.480    -.2365565     .111136
         10  |  -.0399428    .103096    -0.39   0.698    -.2420072    .1621215
         11  |   -.019391   .1153438    -0.17   0.866    -.2454607    .2066787
------------------------------------------------------------------------------
Note: dy/dx for factor levels is the discrete change from the base level.

  Variables that uniquely identify margins: Encouragement

. 
. eststo COA_encour

. 
. logit DCT_ambition i.Female##c.Encouragement qualified_DCT White LawYear  ClerkWork TotalGroup Age ideology Legal_Inter i.CatRan
> k

Iteration 0:   log likelihood = -158.03496  
Iteration 1:   log likelihood = -138.24701  
Iteration 2:   log likelihood =  -138.0856  
Iteration 3:   log likelihood =  -138.0854  
Iteration 4:   log likelihood =  -138.0854  

Logistic regression                             Number of obs     =        234
                                                LR chi2(16)       =      39.90
                                                Prob > chi2       =     0.0008
Log likelihood =  -138.0854                     Pseudo R2         =     0.1262

----------------------------------------------------------------------------------------
          DCT_ambition |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-----------------------+----------------------------------------------------------------
              1.Female |   -.699813   .7766568    -0.90   0.368    -2.222032    .8224065
         Encouragement |   1.305638   1.149327     1.14   0.256     -.947001    3.558276
                       |
Female#c.Encouragement |
                    1  |   1.121354   1.401957     0.80   0.424    -1.626431    3.869138
                       |
         qualified_DCT |   .0341878   .2208795     0.15   0.877    -.3987281    .4671036
                 White |   .4120525   .4318723     0.95   0.340    -.4344016    1.258507
               LawYear |  -.1354196   .3195443    -0.42   0.672     -.761715    .4908758
         ClerkWorkshop |   .4129234   .4948737     0.83   0.404    -.5570113    1.382858
           TotalGroups |   .2786155   .1262976     2.21   0.027     .0310768    .5261543
                   Age |  -.0706166   .0500918    -1.41   0.159    -.1687948    .0275616
              ideology |  -.2617463   .1010545    -2.59   0.010    -.4598096   -.0636831
        Legal_Interest |   .3446976   .1733671     1.99   0.047     .0049043    .6844909
                       |
               CatRank |
                    2  |  -.6835554   .4970952    -1.38   0.169    -1.657844    .2907334
                    3  |  -.7016947   .4164963    -1.68   0.092    -1.518012    .1146231
                    4  |   .0209599   .5026206     0.04   0.967    -.9641584    1.006078
                    5  |  -.4841791   .5531236    -0.88   0.381    -1.568282    .5999233
                    6  |  -.7648875   .5680196    -1.35   0.178    -1.878186    .3484106
                       |
                 _cons |   1.149042   1.664873     0.69   0.490    -2.114049    4.412133
----------------------------------------------------------------------------------------

. margins, dydx(Female) at(Encouragement=(0(.1)1)) plot(recast(line) recastci(rarea))

Average marginal effects                        Number of obs     =        234
Model VCE    : OIM

Expression   : Pr(DCT_ambition), predict()
dy/dx w.r.t. : 1.Female

1._at        : Encouragem~t    =           0

2._at        : Encouragem~t    =          .1

3._at        : Encouragem~t    =          .2

4._at        : Encouragem~t    =          .3

5._at        : Encouragem~t    =          .4

6._at        : Encouragem~t    =          .5

7._at        : Encouragem~t    =          .6

8._at        : Encouragem~t    =          .7

9._at        : Encouragem~t    =          .8

10._at       : Encouragem~t    =          .9

11._at       : Encouragem~t    =           1

------------------------------------------------------------------------------
             |            Delta-method
             |      dy/dx   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
0.Female     |  (base outcome)
-------------+----------------------------------------------------------------
1.Female     |
         _at |
          1  |  -.1452095    .161027    -0.90   0.367    -.4608166    .1703975
          2  |  -.1251423   .1381201    -0.91   0.365    -.3958527    .1455681
          3  |  -.1027113   .1147502    -0.90   0.371    -.3276176    .1221949
          4  |  -.0786684   .0929141    -0.85   0.397    -.2607768      .10344
          5  |   -.053863   .0759259    -0.71   0.478     -.202675     .094949
          6  |  -.0291802   .0681792    -0.43   0.669    -.1628089    .1044485
          7  |  -.0054744    .071741    -0.08   0.939    -.1460842    .1351354
          8  |    .016493    .083284     0.20   0.843    -.1467406    .1797266
          9  |   .0361041   .0978945     0.37   0.712    -.1557657    .2279739
         10  |   .0529174   .1124058     0.47   0.638    -.1673939    .2732287
         11  |   .0666812   .1252789     0.53   0.595    -.1788609    .3122233
------------------------------------------------------------------------------
Note: dy/dx for factor levels is the discrete change from the base level.

  Variables that uniquely identify margins: Encouragement

. 
. eststo DCT_encour

. 
. logit SSC_ambition i.Female##c.Encouragement qualified_SSC White LawYear ClerkWork TotalGroup Age ideology Legal_Inter i.CatRank
>  

Iteration 0:   log likelihood = -143.61359  
Iteration 1:   log likelihood = -130.48569  
Iteration 2:   log likelihood = -130.21426  
Iteration 3:   log likelihood = -130.21372  
Iteration 4:   log likelihood = -130.21372  

Logistic regression                             Number of obs     =        234
                                                LR chi2(16)       =      26.80
                                                Prob > chi2       =     0.0438
Log likelihood = -130.21372                     Pseudo R2         =     0.0933

----------------------------------------------------------------------------------------
          SSC_ambition |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-----------------------+----------------------------------------------------------------
              1.Female |  -.0999099   .8166922    -0.12   0.903    -1.700597    1.500777
         Encouragement |  -.4540139   1.229672    -0.37   0.712    -2.864127      1.9561
                       |
Female#c.Encouragement |
                    1  |   .4545333   1.459023     0.31   0.755    -2.405098    3.314165
                       |
         qualified_SSC |   .0490025   .2255308     0.22   0.828    -.3930298    .4910348
                 White |  -.0006367   .4663373    -0.00   0.999     -.914641    .9133676
               LawYear |  -.3218179   .3290093    -0.98   0.328    -.9666643    .3230285
         ClerkWorkshop |  -.1276681   .4945996    -0.26   0.796    -1.097065    .8417293
           TotalGroups |   .1789614   .1261215     1.42   0.156    -.0682323     .426155
                   Age |  -.0227237    .052834    -0.43   0.667    -.1262765    .0808291
              ideology |  -.1853134   .1124046    -1.65   0.099    -.4056224    .0349955
        Legal_Interest |   .1742501     .18613     0.94   0.349    -.1905581    .5390582
                       |
               CatRank |
                    2  |   .3940242   .5687908     0.69   0.488    -.7207853    1.508834
                    3  |   .8806294   .4437345     1.98   0.047     .0109257    1.750333
                    4  |   1.377978    .496645     2.77   0.006     .4045721    2.351385
                    5  |   2.016902   .5467574     3.69   0.000     .9452774    3.088527
                    6  |   .6586126   .6090848     1.08   0.280    -.5351716    1.852397
                       |
                 _cons |  -.5053747   1.763305    -0.29   0.774    -3.961389    2.950639
----------------------------------------------------------------------------------------

. margins, dydx(Female) at(Encouragement=(0(.1)1)) plot(recast(line) recastci(rarea))

Average marginal effects                        Number of obs     =        234
Model VCE    : OIM

Expression   : Pr(SSC_ambition), predict()
dy/dx w.r.t. : 1.Female

1._at        : Encouragem~t    =           0

2._at        : Encouragem~t    =          .1

3._at        : Encouragem~t    =          .2

4._at        : Encouragem~t    =          .3

5._at        : Encouragem~t    =          .4

6._at        : Encouragem~t    =          .5

7._at        : Encouragem~t    =          .6

8._at        : Encouragem~t    =          .7

9._at        : Encouragem~t    =          .8

10._at       : Encouragem~t    =          .9

11._at       : Encouragem~t    =           1

------------------------------------------------------------------------------
             |            Delta-method
             |      dy/dx   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
0.Female     |  (base outcome)
-------------+----------------------------------------------------------------
1.Female     |
         _at |
          1  |  -.0193153   .1584359    -0.12   0.903    -.3298439    .2912133
          2  |   -.010456   .1321357    -0.08   0.937    -.2694372    .2485253
          3  |  -.0017165   .1077851    -0.02   0.987    -.2129715    .2095385
          4  |   .0068991   .0865684     0.08   0.936    -.1627718    .1765701
          5  |   .0153873   .0707391     0.22   0.828    -.1232589    .1540334
          6  |   .0237446   .0637129     0.37   0.709    -.1011305    .1486196
          7  |   .0319678   .0676021     0.47   0.636    -.1005298    .1644655
          8  |   .0400543   .0802824     0.50   0.618    -.1172963    .1974048
          9  |   .0480013   .0979498     0.49   0.624    -.1439768    .2399794
         10  |   .0558066   .1180121     0.47   0.636    -.1754928     .287106
         11  |   .0634681   .1391227     0.46   0.648    -.2092074    .3361436
------------------------------------------------------------------------------
Note: dy/dx for factor levels is the discrete change from the base level.

  Variables that uniquely identify margins: Encouragement

. 
. eststo SSC_encour

. 
. 
. logit OSC_ambition i.Female##c.Encouragement qualified_OSC White LawYear ClerkWork TotalGroup Age ideology Legal_Inter i.CatRank

note: 2.CatRank != 0 predicts failure perfectly
      2.CatRank dropped and 26 obs not used

Iteration 0:   log likelihood = -90.985626  
Iteration 1:   log likelihood =  -74.82982  
Iteration 2:   log likelihood = -71.558845  
Iteration 3:   log likelihood = -71.461185  
Iteration 4:   log likelihood = -71.460724  
Iteration 5:   log likelihood = -71.460724  

Logistic regression                             Number of obs     =        208
                                                LR chi2(15)       =      39.05
                                                Prob > chi2       =     0.0006
Log likelihood = -71.460724                     Pseudo R2         =     0.2146

----------------------------------------------------------------------------------------
          OSC_ambition |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-----------------------+----------------------------------------------------------------
              1.Female |  -1.568559   1.146854    -1.37   0.171    -3.816351    .6792334
         Encouragement |  -1.724551   1.616915    -1.07   0.286    -4.893647    1.444544
                       |
Female#c.Encouragement |
                    1  |   3.084723   1.979471     1.56   0.119    -.7949693    6.964415
                       |
         qualified_OSC |   .3851233   .3515547     1.10   0.273    -.3039112    1.074158
                 White |   .6642521   .7550494     0.88   0.379    -.8156176    2.144122
               LawYear |  -.2454124   .4618304    -0.53   0.595    -1.150583    .6597586
         ClerkWorkshop |  -2.456095    1.08126    -2.27   0.023    -4.575327   -.3368641
           TotalGroups |  -.0241462   .1665425    -0.14   0.885    -.3505636    .3022712
                   Age |   .0313359   .0579643     0.54   0.589    -.0822721     .144944
              ideology |  -.1786866   .1563724    -1.14   0.253    -.4851709    .1277976
        Legal_Interest |  -.2096117   .2706813    -0.77   0.439    -.7401372    .3209139
                       |
               CatRank |
                    2  |          0  (empty)
                    3  |   1.004348   .7008794     1.43   0.152    -.3693509    2.378046
                    4  |   2.694925   .7158876     3.76   0.000     1.291811    4.098039
                    5  |    2.70412   .7218575     3.75   0.000     1.289305    4.118935
                    6  |   1.793268   .8375806     2.14   0.032     .1516399    3.434896
                       |
                 _cons |  -3.193121   2.216881    -1.44   0.150    -7.538128    1.151886
----------------------------------------------------------------------------------------

. margins, dydx(Female) at(Encouragement=(0(.1)1)) plot(recast(line) recastci(rarea))

Average marginal effects                        Number of obs     =        208
Model VCE    : OIM

Expression   : Pr(OSC_ambition), predict()
dy/dx w.r.t. : 1.Female

1._at        : Encouragem~t    =           0

2._at        : Encouragem~t    =          .1

3._at        : Encouragem~t    =          .2

4._at        : Encouragem~t    =          .3

5._at        : Encouragem~t    =          .4

6._at        : Encouragem~t    =          .5

7._at        : Encouragem~t    =          .6

8._at        : Encouragem~t    =          .7

9._at        : Encouragem~t    =          .8

10._at       : Encouragem~t    =          .9

11._at       : Encouragem~t    =           1

------------------------------------------------------------------------------
             |            Delta-method
             |      dy/dx   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
0.Female     |  (base outcome)
-------------+----------------------------------------------------------------
1.Female     |
         _at |
          1  |  -.1708753   .1346149    -1.27   0.204    -.4347157    .0929651
          2  |  -.1361929   .1101853    -1.24   0.216    -.3521521    .0797663
          3  |   -.102019   .0888448    -1.15   0.251    -.2761517    .0721136
          4  |  -.0683767    .071275    -0.96   0.337    -.2080731    .0713196
          5  |  -.0352809   .0585676    -0.60   0.547    -.1500713    .0795095
          6  |  -.0027382   .0521555    -0.05   0.958    -.1049612    .0994847
          7  |   .0292531    .052806     0.55   0.580    -.0742448    .1327511
          8  |   .0607042    .059528     1.02   0.308    -.0559686    .1773769
          9  |   .0916353   .0704792     1.30   0.194    -.0465013     .229772
         10  |   .1220764   .0843294     1.45   0.148    -.0432062     .287359
         11  |   .1520656   .1004429     1.51   0.130    -.0447988    .3489301
------------------------------------------------------------------------------
Note: dy/dx for factor levels is the discrete change from the base level.

  Variables that uniquely identify margins: Encouragement

. 
. eststo OSC_encour

. 
. clear

. 
. log close
      name:  <unnamed>
       log:  C:\Users\Dr. Badas\Dropbox\1 - Research\98 - Coauthored Projects\1 - Gender and Law Clerk Encouragement\2- Data and C
> ode\First Survey\BadasStaufferJLCreplication.log
  log type:  text
 closed on:   7 Dec 2021, 15:10:48
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